| Full text | |
| Author(s): |
Total Authors: 4
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| Affiliation: | [1] Univ Estadual Campinas, Sch Elect & Comp Engn, BR-13083852 Campinas, SP - Brazil
[2] Univ Estadual Campinas, Inst Comp, BR-13083970 Campinas, SP - Brazil
Total Affiliations: 2
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| Document type: | Journal article |
| Source: | IEEE ACCESS; v. 6, p. 24829-24836, 2018. |
| Web of Science Citations: | 0 |
| Abstract | |
We propose a new method to improve median plane sound localization performance using a nonlinear representation of head-related transfer functions (HRTFs) and a recommender system. First, we reduce the dimensionality of an HRTF data set with multiple subjects using manifold learning in conjunction with a customized intersubject graph which takes into account relevant prior knowledge of HRTFs. Then, we use a sound localization model to estimate a subject's localization performance in terms of polar error and quadrant error rate. These metrics are merged to form a single rating per HRTF pair that we feed into a recommender system. Finally, the recommender system takes the low-dimensional HRTF representation as well as the ratings obtained from the localization model to predict the best HRTF set, possibly constructed by mixing HRTFs from different individuals, that minimizes a subject's localization error. The simulation results show that our method is capable of choosing a set of HRTFs that improves the median plane localization performance with respect to the mean localization performance using non-individualized HRTFs. Moreover, the localization performance achieved by our HRTF recommender system shows no significant difference to the localization performance observed with the best matching non-individualized HRTFs but with the advantage of not having to perform listening tests with all individuals' HRTFs from the database. (AU) | |
| FAPESP's process: | 12/50468-6 - Vision for the blind: translating 3D visual concepts into 3D auditory clues |
| Grantee: | Siome Klein Goldenstein |
| Support Opportunities: | Research Grants - Research Partnership for Technological Innovation - PITE |
| FAPESP's process: | 14/14630-9 - Machine learning for signal processing applied to spatial audio |
| Grantee: | Felipe Leonel Grijalva Arévalo |
| Support Opportunities: | Scholarships in Brazil - Doctorate |
| FAPESP's process: | 13/21349-1 - Vision for the blind: translating 3D visual concepts into 3D auditory clues |
| Grantee: | Felipe Leonel Grijalva Arévalo |
| Support Opportunities: | Scholarships in Brazil - Master |